Driving Insights Out of Connected Data to Transform Project Management

We live in a connected world! Project teams often struggle to knit together the disparate information that is stored across different software systems. But in reality, all of these sources of data are connected. Our challenge is joining them together to derive insights that will enable us to move from descriptive analytics towards predictive analytics and prescriptive analytics where we are able to positively influence the future.

The London Project Data Analytics Meetup is joining forces with the Neo4J Meetup to explore how graph databases may help to transform project management.

We'll start with a 30 minute introduction to Neo4j and graph databases. In this talk Mark will explain what graph databases are, how they can be used, what purposes that they serve. During this session we will present, explain and discuss introductory topics that require no prior knowledge on graph databases at all. We'll even have a quick demo to get you excited about the power of graphs.

James will provide us with a demo based upon some real world examples. He will walk us through the process of how to break down the business problem, develop the data model and structure the graph. He will then walk us through NASA's approach to lessons learned and show how we can use what they’ve done to improve other areas of project delivery. We will explore the idea of connected data using a latent Dirichlet Allocation (LDA) and experiment with alternative use cases for how to exploit the value that such an algorithm could provide.

We’ll also have a brief interactive session to explore how connections could be forged from other datasets and the value that this could provide.

Mark Needham

Mark is a graph advocate and field engineer for Neo Technology, the company behind the Neo4j graph database. As a field engineer, Mark helps customers embrace graph data and Neo4j by building sophisticated solutions to challenging data problems.

James Smith

Dr James Smith is the Chief Technology Officer and lead Data Scientist within Projecting Success and has a broad remit spanning data analysis through to machine learning; he has a passion for using emerging methods to transform how projects are delivered. He has an applied mathematics PhD and specialised in Orthogonal Polynomials and the Painlevé equations. He spent 2 years lecturing mathematics at the University of Kent before making the natural transition to Data Scientist in 2017.

18:30: Mark Needham
Break: Food and drinks
19:30: James Smith
Questions
20:30: Drinks in the bar and close.